Food allergy: a practical update from the gastroenterological viewpoint
Bibliographic record
Abstract
OBJECTIVE: To present an up-to-date and critical review regarding food allergies, focusing mainly on treatment and prevention. SOURCES: Review of published literature searched on MEDLINE database; those data which were the most up-to-date and representative were selected (2000-2006). The search included the European Society of Pediatric Gastroenterology, Hepatology and Nutrition (ESPGHAN) and the American Academy of Pediatrics (AAP). SUMMARY OF THE FINDINGS: The prevalence of allergic diseases has increased over the last decades, and food allergy seems to be part of this increase. Food allergy is much more common in pediatrics and has a significant medical, financial and social impact on young children and their families. Treatment and prevention of food allergy is a major challenge for public health, scientific and medical communities. There is a lot of misinformation and the medical management of this condition is still discussable. We present and discuss the guidelines regarding criteria for the prevention of food allergy and atopic diseases published by the Nutrition Committees of ESPGHAN jointly with the European Society for Pediatric Allergy and Clinical Immunology (ESPACI) and AAP. CONCLUSION: The overdiagnosis of food allergy is quite prevalent. There is a need for standardization of definitions and diagnostic procedures. The primary goal of therapy should be to first establish effective means of preventing food allergies. There is a need for accurate diagnostic methods to confirm or rule out the diagnosis. Patients need appropriate treatment by eliminating foods that cause symptoms, while avoiding the nutritional side effects and the cost of inappropriate diets.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.005 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.010 | 0.007 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.005 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.004 | 0.002 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".